A1 Refereed original research article in a scientific journal

Prediction of bullying at work: A data-driven analysis of the Finnish public sector cohort study




AuthorsErvasti Jenni, Pentti Jaana, Seppälä Piia, Ropponen Anniina, Virtanen Marianna, Elovainio Marko, Chandola Tarani, Kivimäki Mika, Airaksinen Jaakko

PublisherElsevier Ltd

Publication year2023

JournalSocial Science and Medicine

Journal name in sourceSocial Science and Medicine

Article number115590

Volume317

DOIhttps://doi.org/10.1016/j.socscimed.2022.115590

Web address https://doi.org/10.1016/j.socscimed.2022.115590

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/178774500


Abstract
Aim

To determine the extent to which change in (i.e., start and end of) workplace bullying can be predicted by employee responses to standard workplace surveys.

Methods

Responses to an 87-item survey from 48,537 Finnish public sector employees at T1 (2017–2018) and T2 (2019–2020) were analyzed with least-absolute-shrinkage-and-selection-operator (LASSO) regression. The predictors were modelled both at the individual- and the work unit level. Outcomes included both the start and the end of bullying. Predictive performance was evaluated with C-indices and density plots.

Results

The model with best predictive ability predicted the start of bullying with individual-level predictors, had a C-index of 0.68 and included 25 variables, of which 6 remained in a more parsimonious model: discrimination at work unit, unreasonably high workload, threat that some work tasks will be terminated, working in a work unit where everyone did not feel they are understood and accepted, having a supervisor who was not highly trusted, and a shorter time in current position. Other models performed even worse, either from the point of view of predictive performance, or practical useability.

Discussion

While many bivariate associations between socioeconomic characteristics, work characteristics, leadership, team climate, and job satisfaction were observed, reliable individualized detection of individuals at risk of becoming bullied at workplace was not successful. The predictive performance of the developed risk scores was suboptimal, and we do not recommend their use as an individual-level risk prediction tool. However, they might be useful tool to inform decision-making when planning the contents of interventions to prevent bullying at an organizational level.

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Last updated on 2025-27-03 at 21:47